CN115179445B - CNC (computer numerical control) processing method for vacuum cavity sealing piece based on space positioning error model - Google Patents

CNC (computer numerical control) processing method for vacuum cavity sealing piece based on space positioning error model Download PDF

Info

Publication number
CN115179445B
CN115179445B CN202210953009.9A CN202210953009A CN115179445B CN 115179445 B CN115179445 B CN 115179445B CN 202210953009 A CN202210953009 A CN 202210953009A CN 115179445 B CN115179445 B CN 115179445B
Authority
CN
China
Prior art keywords
error
coordinate
machining
representing
positioning error
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202210953009.9A
Other languages
Chinese (zh)
Other versions
CN115179445A (en
Inventor
沈金惠
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Yongdeli Technology Wuxi Co ltd
Original Assignee
Yongdeli Technology Wuxi Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Yongdeli Technology Wuxi Co ltd filed Critical Yongdeli Technology Wuxi Co ltd
Priority to CN202210953009.9A priority Critical patent/CN115179445B/en
Publication of CN115179445A publication Critical patent/CN115179445A/en
Application granted granted Critical
Publication of CN115179445B publication Critical patent/CN115179445B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • BPERFORMING OPERATIONS; TRANSPORTING
    • B28WORKING CEMENT, CLAY, OR STONE
    • B28DWORKING STONE OR STONE-LIKE MATERIALS
    • B28D5/00Fine working of gems, jewels, crystals, e.g. of semiconductor material; apparatus or devices therefor
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B26HAND CUTTING TOOLS; CUTTING; SEVERING
    • B26DCUTTING; DETAILS COMMON TO MACHINES FOR PERFORATING, PUNCHING, CUTTING-OUT, STAMPING-OUT OR SEVERING
    • B26D1/00Cutting through work characterised by the nature or movement of the cutting member or particular materials not otherwise provided for; Apparatus or machines therefor; Cutting members therefor
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

The invention discloses a CNC processing method of a vacuum cavity sealing piece based on a space positioning error model, which comprises the following steps: s1, constructing a space positioning error model of a workpiece based on a multi-body system theory; s2, identifying geometric errors of the rotating shaft through a laser interferometer; s3, decomposing the space positioning error; s4, constructing a compensation data model of the space positioning error; s5, performing compensation quality control on the correction coefficient based on a second-generation non-dominant sorting genetic algorithm; s6, starting a range finder to calculate the distance between the machining tool and the workpiece; s7, the controller controls the clamp to slide to a designated position; s8, detecting a linkage track of the rotating shaft according to a preset period; s9, updating the geometric error correction data to an error database regularly. The multi-body system theory obtained through abstraction of the numerical control machine tool machining center can construct an accurate space positioning error model without being limited by the structure and the motion complexity, and the machining precision of the sealing element is greatly improved.

Description

CNC (computer numerical control) processing method for vacuum cavity sealing piece based on space positioning error model
Technical Field
The invention relates to the technical field of vacuum cavity sealing piece machining, in particular to a CNC machining method for a vacuum cavity sealing piece based on a space positioning error model.
Background
With the continuous progress of society, new materials, automation, computer and other scientific technologies have achieved breakthrough results, and the machine manufacturing industry has accordingly made historic changes, and has rapidly developed towards high efficiency, high precision and high intelligence.
The atmosphere in which we live is filled with a large amount of nitrogen, oxygen and other various gas molecules, and when these gas molecules move to the surface of the object, a part of them adhere to the surface of the object. This does not affect how much in daily life, but these subtle changes cause various troubles in the production process of semiconductor devices requiring extremely high environmental demands. Semiconductor devices comprise a plurality of layers of various materials that, if mixed with gaseous molecules between the layers of different materials, can destroy the electrical or optical properties of the device. Therefore, the higher the vacuum degree in the production process, the better the performance of the manufactured semiconductor device.
The vacuum system is an air extraction system for ensuring that the reaction cavity of the vacuum system obtains the vacuum pressure required by the process, and is a decisive factor for meeting the specific pressure condition required by the semiconductor manufacturing process, so that the performance optimization of the vacuum system is still an important means for improving the semiconductor manufacturing technology.
Along with industrial development and discipline fusion, the application scene of the vacuum technology is greatly enriched, and the digitization and intelligent degree of related products and scientific instruments are obviously improved; the application conditions of the technological front and the emerging fields are more severe, and the technical attack difficulty and risk are obviously increased. The vacuum cavity is used as one of the basic components of the vacuum technology, the improvement of the manufacturing level and the process optimization of the vacuum cavity become important supports for the construction of important scientific devices and the development of high-end equipment, and represent the development direction of the industrial basic commonality technology. The vacuum cavity is used as one of important parts in a semiconductor equipment system, and needs to meet the application conditions of complicated structure modeling, high and low temperature circulation, ultrahigh pressure, high vacuum circulation, irradiation damage, high temperature ablation, gravel erosion, chemical corrosion and the like, and the tightness of the vacuum cavity has a decisive influence on the performance of semiconductor devices.
The accuracy in the machining process determines the excellent degree of the sealing performance of the sealing element, the processes of high-automation intelligent conveying, detection, cutter machining and the like are realized in the CNC machining process of the metal sealing element at present, the machining accuracy degree is ensured through a numerical control system, but due to certain abrasion and deviation of a numerical control machine tool and various equipment in operation, a plurality of errors still exist in the long-term machining process, the sealing performance of the sealing element is influenced, and finally the performance of a vacuum cavity is influenced. Therefore, it is necessary to further improve the accuracy and efficiency of error detection in the numerical control system, and ensure the performance of the sealing member and the vacuum chamber.
Patent number CN106842922B discloses a numerical control machining error optimization method, which comprehensively considers a plurality of factors influencing numerical control machining, predicts machining state characteristic parameters and machining errors by using a mathematical fitting principle and a neural network model, carries out partial fine adjustment on a numerical control program according to the obtained prediction errors, and directly compensates the machining errors, thereby achieving the aim of optimizing the numerical control machining errors. However, the method still has certain defects that the position of a processing mechanism such as a machine tool of a processing center is not limited, and the processing in the processing process is positioned with high precision.
For the problems in the related art, no effective solution has been proposed at present.
Disclosure of Invention
Aiming at the problems in the related art, the invention provides a CNC processing method for a vacuum cavity sealing member based on a space positioning error model, so as to overcome the technical problems in the prior art.
For this purpose, the invention adopts the following specific technical scheme:
CNC machining method for vacuum cavity sealing piece based on space positioning error model comprises the following steps:
s1, constructing a space positioning error model of a workpiece based on a multi-body system theory;
s2, identifying geometric errors of the rotating shaft through a laser interferometer to form an error database;
s3, decomposing the space positioning error;
s4, combining a sag error compensation function of the numerical control system to construct a compensation data model of the space positioning error;
s5, compensating quality control is carried out on the correction coefficient based on a second-generation non-dominant sorting genetic algorithm, and optimization of the correction coefficient is achieved;
s6, starting a range finder to calculate the distance between the machining tool and the workpiece, and outputting a current position signal of the workpiece by combining the optimized correction coefficient;
s7, the controller controls the clamp to slide to a designated position, and a machining tool is used for precisely machining a workpiece;
s8, detecting a linkage track of the rotating shaft according to a preset period, setting a linkage track positioning error threshold value, and detecting the machining precision of the workpiece;
s9, updating the geometric error correction data to an error database regularly.
Further, the method for constructing the spatial positioning error model of the workpiece based on the multi-body system theory comprises the following steps:
s11, abstracting a mechanical system of a machining center into a multi-body system;
s12, constructing a topological graph and a low-order body array description body-body association relation;
s13, establishing a sub-coordinate system fixed on the body for each body, and describing the pose between the bodies according to the pose relation between the sub-coordinate systems;
s14, utilizing a 4x4 order D-H matrix to realize coordinate transformation of points in space among all sub-coordinate systems;
s15, constructing an actual pose matrix between two adjacent bodies according to the feature matrices of the two adjacent bodies;
s16, constructing pose matrixes of any two bodies;
s16, constructing an ideal coordinate array and an actual coordinate matrix of a machining tool tip center point in a machining tool body sub-coordinate system in the machining center;
s17, constructing a spatial error model of the machining center by utilizing the difference value between the ideal coordinate and the actual coordinate of the center point of the tip of the machining tool.
Further, the expression of the spatial error model is:
Figure BDA0003788415570000031
wherein e represents a spatial error model;
P wS representing an ideal coordinate array of a machining tool tip center point P in an S coordinate system;
P′ wS representing the actual coordinate array of the center point P of the tip of the machining tool in the S coordinate system, and
Figure BDA0003788415570000041
Figure BDA0003788415570000042
representing a J coordinate feature matrix;
T SJ representing pose matrixes of an S coordinate system and a J coordinate system;
P tJ representing an ideal coordinate array of a machining tool tip center point P in a J coordinate system;
l represents the displacement amount, and n represents the number of sub-coordinate systems.
4, identifying the geometric error of the rotating shaft by a laser interferometer to form an error database, wherein the method comprises the following steps:
s21, mounting a double-frequency laser interferometer in the direction of a coordinate axis of a machine tool to be measured;
s22, adjusting the laser head to enable the measuring axis to coincide with or be parallel to the displacement axis of the machine tool, and pre-aligning the light path;
s23, inputting measurement parameters after laser preheating, and moving the machine tool for measurement according to a preset measurement program;
s24, identifying geometric errors in a working section of the numerical control machine tool by adopting a nine-line method;
s25, synthesizing various geometric error data to construct an error database.
Further, the identification of geometric errors in the working section of the digital machine tool by adopting the nine-line method comprises the following steps:
s241, establishing a workbench coordinate model, and setting a point A (X i ,Y i ,Z i );
S242, when the fixed point A moves along the X-axis coordinate, measuring an X-direction movement error value, wherein the expression comprises:
Figure BDA0003788415570000043
represented by matrix, let
x }=[δ x (x) δ y (x) δ z (x) ε x (x) ε y (x) ε z (x)] T Then
{Δ(X)}=[E x ]{δ x }
Figure BDA0003788415570000051
Wherein { delta } x -represents a set of x-direction errors;
x (x) Representing a linear displacement error;
y (x) And delta z (x) Respectively representing straightness errors in the y direction and the z direction;
ε x (x) Representing a roll error;
ε y (x) Representing pitch error;
ε z (x) Representing yaw error;
E x representing a coefficient matrix;
x, Y, Z the X-axis, Y-axis, Z-axis in the coordinate system, respectively;
X i 、Y i 、Z i coordinate values respectively representing the point a;
Figure BDA0003788415570000052
and->
Figure BDA0003788415570000053
X, Y, Z straightness is respectively expressed;
i represents that the value of the number of the coordinate axes is (1, 2, 3);
t represents matrix transposition;
s243, when the fixed point A moves along the Y-axis coordinate, measuring a Y-direction movement error value;
s244, when the fixed point A moves along the Z-axis coordinate, measuring a Z-direction movement error value;
s245, calculating the perpendicularity error by using the straightness error of each axis.
Further, the spatial positioning error is decomposed into a linear correlation and a nonlinear correlation.
Further, the method for constructing the spatial positioning error compensation data model by combining the sag error compensation function of the numerical control system comprises the following steps:
s41, correcting an ideal numerical control instruction by combining a linear related space positioning error;
s42, downloading the corrected ideal numerical control instruction to each controller, and outputting a cutter route;
s43, moving the processing cutter to a processing point according to the cutter route;
s44, constructing an actual movement route of the machining tool in a body coordinate system, and drawing a tool path;
s45, checking the tool path and the tool path, constructing a compensation data model of the space positioning error, and outputting a correction coefficient.
Further, the compensation quality control is performed on the correction coefficient based on the second-generation non-dominant sorting genetic algorithm to realize the optimization of the correction coefficient, and the method comprises the following steps:
s51, setting algorithm parameters and correction coefficient variation ranges;
s52, coding the machining center controller, and initializing a plurality of controller prevention schemes meeting constraints to form a population;
s53, calculating the time delay from the average processing tool to the controller, the time delay between the maximum controllers, the failure proportion of the average control path and the number of slave controllers of the average processing tool corresponding to each individual according to a preset data model and an objective function;
s54, performing non-dominant solution sequencing on the current population, and respectively calculating the crowding distance of individuals in each layer;
s55, selecting, crossing and mutating the population to generate a child population;
s56, merging the parent population and the offspring population according to elite retention strategy to obtain a next generation population;
s57, if the iteration number reaches the maximum iteration number, stopping iteration and outputting the optimal correction coefficient.
Further, the expression of the objective function is:
minF(CP)=[f 1 (CP),f 2 (CP),f 3 (CP),-f 4 (CP)]
where minF (CP) represents the value of the objective function;
f 1 (CP) represents minimizing the time of the machining tool to the controllerExtending;
f 2 (CP) means minimizing the time delay between controllers;
f 3 (CP) means minimizing a control path failure rate;
f 4 (CP) means maximizing the average machining tool possession slave controller number;
CP denotes a deployment scenario of the controller.
Further, the calculation formula of the congestion distance includes:
Figure BDA0003788415570000071
wherein I (d) K ) Representing a crowding distance;
I(d 0 ) Representing an initial congestion distance;
i (k) m represents the value of the mth objective function of the kth individual in I;
Figure BDA0003788415570000072
representing the maximum of the mth objective function;
Figure BDA0003788415570000073
representing the minimum of the mth objective function;
m represents the number of objective functions.
The beneficial effects of the invention are as follows: the multi-body system theory obtained through abstraction of the numerical control machine tool machining center can construct an accurate space positioning error model without being limited by the structure and the motion complexity, and high-precision calculation, analysis, detection, compensation and control are carried out on the machining error of the machine tool; geometric error identification by matching with a laser interferometer and a nine-wire method is carried out, so that the detection precision and the identification efficiency of the error are greatly improved, the numerical control machining precision is further improved, and the vacuum cavity is ensured to have good sealing performance.
The invention integrates a second-generation non-dominant sorting genetic algorithm to carry out compensation quality control on the correction coefficient, and can further test and optimize and improve the error correction, thereby improving the processing precision of the workpiece to a greater extent, and the response delay between the processing controller and the processing cutter and other equipment can be reduced by calculating and optimizing the time delay among the equipment, thereby improving the efficiency of numerical control processing;
in addition, the invention has universality, is also suitable for the production and processing of other high-precision parts, plays a positive role in improving the product quality, improving the production efficiency, reducing the production cost and the like, and therefore, brings more social and economic benefits and has good market prospect.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a vacuum cavity seal CNC machining method based on a spatial positioning error model according to an embodiment of the present invention.
Detailed Description
According to an embodiment of the invention, a CNC machining method for a vacuum cavity sealing piece based on a space positioning error model is provided.
The invention will be further described with reference to the accompanying drawings and detailed description, as shown in fig. 1, a vacuum cavity seal CNC machining method based on a spatial positioning error model according to an embodiment of the invention, the method comprises the following steps:
s1, constructing a space positioning error model of a workpiece based on a multi-body system theory;
the establishment of an accurate spatial error model of the machining center is the basis of error identification. At present, a plurality of methods such as a triangle geometry method, an error matrix method, a neural network method, a rigid body kinematics method, a multi-body system theory method and the like are available for establishing a space error model. However, only the multi-body system theory method comprehensively considers various influencing factors and coupling relations of complex system movement, solves the problems of accuracy, universality and automation of the spatial error modeling of the machining center, and other methods have certain limitations. Therefore, the invention is based on the theory of a multi-body system and uses the pose matrix to build a space error model of the processing center.
Wherein, step S1 comprises the following steps:
s11, abstracting a mechanical system of a machining center into a multi-body system;
s12, constructing a topological graph and a low-order body array description body-body association relation;
s13, establishing a sub-coordinate system fixed on the body for each body, and describing the pose between the bodies according to the pose relation between the sub-coordinate systems;
s14, utilizing a 4x4 order D-H matrix (Denavit-Hartenberg) to realize coordinate transformation of points in space among all sub-coordinate systems;
s15, constructing an actual pose matrix between two adjacent bodies according to the feature matrices of the two adjacent bodies;
s16, constructing pose matrixes of any two bodies;
s16, constructing an ideal coordinate array and an actual coordinate matrix of a machining tool tip center point in a machining tool body sub-coordinate system in the machining center;
s17, constructing a spatial error model of the machining center by utilizing the difference value between the ideal coordinate and the actual coordinate of the center point of the tip of the machining tool, wherein the expression is as follows:
Figure BDA0003788415570000091
wherein e represents a spatial error model;
P wS representing an ideal coordinate array of a machining tool tip center point P in an S coordinate system;
P′ wS representing the actual coordinate array of the center point P of the tip of the machining tool in the S coordinate system, and
Figure BDA0003788415570000092
Figure BDA0003788415570000093
representing a J coordinate feature matrix;
T SJ representing pose matrixes of an S coordinate system and a J coordinate system;
P tJ representing an ideal coordinate array of a machining tool tip center point P in a J coordinate system;
l represents the displacement amount, and n represents the number of sub-coordinate systems.
S2, identifying geometric errors of the rotating shaft through a laser interferometer to form an error database;
for a three-axis spatial coordinate system, if an object moves along a certain coordinate axis, there are 6 degrees of freedom in its motion, then there are 6 geometric error components, namely a straightness error along 3 coordinate axes and a rotational error for 3 coordinate axes.
Wherein, step S2 includes the following steps:
s21, mounting a double-frequency laser interferometer in the direction of a coordinate axis of a machine tool to be measured;
s22, adjusting the laser head to enable the measuring axis to coincide with or be parallel to the displacement axis of the machine tool, and pre-aligning the light path;
s23, inputting measurement parameters after laser preheating, and moving the machine tool for measurement according to a preset measurement program;
s24, identifying geometric errors in a working section of the numerical control machine tool by adopting a nine-line method;
the numerical control machine tool error identification methods are 22-wire method, 15-wire method, 14-wire method, 9-wire method and the like, and the former methods have low measurement efficiency and difficult adjustment of a measurement light path, so that certain errors can be caused. 9, the modeling method of the line method identification method is simple, convenient and universal; during modeling, uncertain assumption conditions are eliminated; the difficulty of light path adjustment is reduced, the workload is reduced, and 21 geometric errors in the whole working interval of the numerical control machine tool can be accurately identified by adopting a 9-line method.
The method for identifying the geometric errors of the working section of the digital machine tool by adopting the nine-wire method comprises the following steps:
s241, establishing a workbench coordinate model, and setting a point A (X i ,Y i ,Z i );
S242, when the fixed point A moves along the X-axis coordinate, measuring an X-direction movement error value, wherein the expression comprises:
Figure BDA0003788415570000101
represented by matrix, let
x }=[δ x (x) δ y (x) δ z (x) ε x (x) ε y (x) ε z (x)] T
Then
{Δ(X)}=[E x ]{δ x }
Figure BDA0003788415570000111
Wherein { delta } x -represents a set of x-direction errors;
x (x) Representing a linear displacement error;
y (x) And delta z (x) Respectively representing straightness errors in the y direction and the z direction;
ε x (x) Representing a roll error;
ε y (x) Representing pitch error;
ε z (x) Representing yaw error;
E x representing a coefficient matrix;
x, Y, Z the X-axis, Y-axis, Z-axis in the coordinate system, respectively;
X i 、Y i 、Z i coordinate values respectively representing the point a;
Figure BDA0003788415570000112
and->
Figure BDA0003788415570000113
X, Y, Z straightness is respectively expressed;
i represents that the value of the number of the coordinate axes is (1, 2, 3);
t represents matrix transposition;
s243, when the fixed point A moves along the Y-axis coordinate, measuring a Y-direction movement error value;
s244, when the fixed point A moves along the Z-axis coordinate, measuring a Z-direction movement error value;
s245, calculating the perpendicularity error by using the straightness error of each axis.
S25, synthesizing various geometric error data to construct an error database.
S3, decomposing the space positioning error, and decomposing the space positioning error into linear correlation and nonlinear correlation.
S4, combining a sag error compensation function of the numerical control system to construct a compensation data model of the space positioning error;
the existing numerical control machine tool error compensation method mainly comprises hardware compensation and software compensation. Because of the inherent defects of hardware compensation, the invention adopts a software compensation method based on an error model to correct an ideal numerical control instruction, and drives a numerical control machine tool through the numerical control instruction value after correction, so that the center of the tool of the machine tool moves to a machining point accurately, and error compensation is realized.
Wherein, step S4 includes the following steps:
s41, correcting an ideal numerical control instruction by combining a linear related space positioning error;
s42, downloading the corrected ideal numerical control instruction to each controller, and outputting a cutter route;
s43, moving the processing cutter to a processing point according to the cutter route;
s44, constructing an actual movement route of the machining tool in a body coordinate system, and drawing a tool path;
s45, checking the tool path and the tool path, constructing a compensation data model of the space positioning error, and outputting a correction coefficient.
S5, compensating quality control is carried out on the correction coefficient based on a second-generation non-dominant sorting genetic algorithm (NSGA-II algorithm), and optimization of the correction coefficient is achieved;
wherein, step S5 includes the following steps:
s51, setting algorithm parameters and correction coefficient variation ranges;
s52, coding the machining center controller, and initializing a plurality of controller prevention schemes meeting constraints to form a population;
s53, calculating the time delay from the average processing tool to the controller, the time delay between the maximum controllers, the failure proportion of the average control path and the number of slave controllers of the average processing tool corresponding to each individual according to a preset data model and an objective function;
wherein, the expression of the objective function is:
minF(CP)=[f 1 (CP),f 2 (CP),f 3 (CP),-f 4 (CP)]
where minF (CP) represents the value of the objective function;
f 1 (CP) means minimizing the time delay of the machining tool to the controller, expressed as:
Figure BDA0003788415570000131
f 2 (CP) represents minimizing the latency between controllers, expressed as:
Figure BDA0003788415570000132
f 3 (CP) represents a minimized control-path failure ratio, expressed as:
Figure BDA0003788415570000133
f 4 (CP) means maximizing the average machining tool possession slave controller number expressed as:
Figure BDA0003788415570000134
CP represents a deployment scenario for the controller;
i, j each represent the number of nodes;
c i a number representing a machining tool node in which the controller in the ith control domain is located;
c j a number indicating a machining tool node in which the controller in the jth control domain is located;
x ij =1 means that the master controller of the machining tool i is the controller c in the j-th control domain i Otherwise x ij =0;
y ij =1 denotes the controller c in the j-th control domain j Is the slave controller of the machining tool i, otherwise y ij =0;
e i Representing the number of control paths each network element is located on;
k represents the number and numbering of control domains in the network topology;
n represents the number of machining tools;
w represents the number of physical network elements including the processing tool and the link;
s represents the number of paths between controllers;
s54, performing non-dominant solution sequencing on the current population, and respectively calculating the crowding distance of individuals in each layer;
wherein, the calculation formula of the crowding distance comprises:
Figure BDA0003788415570000141
wherein I (d) K ) Representing a crowding distance;
I(d 0 ) Representing an initial congestion distance;
i (k) m represents the value of the mth objective function of the kth individual in I;
Figure BDA0003788415570000142
representing the maximum of the mth objective function;
Figure BDA0003788415570000143
representing the minimum of the mth objective function;
m represents the number of objective functions.
S55, selecting, crossing and mutating the population to generate a child population;
s56, merging the parent population and the offspring population according to elite retention strategy to obtain a next generation population;
s57, if the iteration number reaches the maximum iteration number, stopping iteration and outputting the optimal correction coefficient.
S6, starting a range finder to calculate the distance between the machining tool and the workpiece, and outputting a current position signal of the workpiece by combining the optimized correction coefficient;
s7, the controller controls the clamp to slide to a designated position, and a machining tool is used for precisely machining a workpiece;
s8, detecting a linkage track of the rotating shaft according to a preset period, setting a linkage track positioning error threshold value, and detecting the machining precision of the workpiece;
s9, updating the geometric error correction data to an error database regularly.
In summary, by means of the technical scheme, the multi-body system theory obtained through abstraction of the numerical control machine tool machining center can construct an accurate space positioning error model without being limited by the structure and the motion complexity, and high-precision calculation, analysis, detection, compensation and control of the machine tool machining error can be performed; geometric error identification by matching with a laser interferometer and a nine-wire method is carried out, so that the detection precision and the identification efficiency of the error are greatly improved, the numerical control machining precision is further improved, and the vacuum cavity is ensured to have good sealing performance.
The invention integrates a second-generation non-dominant sorting genetic algorithm to carry out compensation quality control on the correction coefficient, and can further test and optimize and improve the error correction, thereby improving the processing precision of the workpiece to a greater extent, and the response delay between the processing controller and the processing cutter and other equipment can be reduced by calculating and optimizing the time delay among the equipment, thereby improving the efficiency of numerical control processing;
in addition, the invention has universality, is also suitable for the production and processing of other high-precision parts, plays a positive role in improving the product quality, improving the production efficiency, reducing the production cost and the like, and therefore, brings more social and economic benefits and has good market prospect.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.

Claims (7)

1. CNC machining method for vacuum cavity sealing piece based on space positioning error model is characterized by comprising the following steps:
s1, constructing a space positioning error model of a workpiece based on a multi-body system theory; the method for constructing the spatial positioning error model of the workpiece based on the multi-body system theory comprises the following steps:
s11, abstracting a mechanical system of a machining center into a multi-body system;
s12, constructing a topological graph and a low-order body array description body-body association relation;
s13, establishing a sub-coordinate system fixed on the body for each body, and describing the pose between the bodies according to the pose relation between the sub-coordinate systems;
s14, utilizing a 4x4 order D-H matrix to realize coordinate transformation of points in space among all sub-coordinate systems;
s15, constructing an actual pose matrix between two adjacent bodies according to the feature matrices of the two adjacent bodies;
s16, constructing pose matrixes of any two bodies;
s16, constructing an ideal coordinate array and an actual coordinate matrix of a machining tool tip center point in a machining tool body sub-coordinate system in the machining center;
s17, constructing a spatial error model of the machining center by utilizing the difference value between the ideal coordinate and the actual coordinate of the center point of the tip of the machining tool; the expression of the spatial error model is as follows:
Figure FDA0003788415560000011
wherein e represents a spatial error model;
P wS representing an ideal coordinate array of a machining tool tip center point P in an S coordinate system;
P′ wS representing the actual coordinate array of the center point P of the tip of the machining tool in the S coordinate system, and
Figure FDA0003788415560000012
Figure FDA0003788415560000013
representing a J coordinate feature matrix;
T SJ representing pose matrixes of an S coordinate system and a J coordinate system;
P tJ representing an ideal coordinate array of a machining tool tip center point P in a J coordinate system;
l represents a displacement amount;
n represents the number of sub-coordinate systems;
s2, identifying geometric errors of the rotating shaft through a laser interferometer to form an error database;
s3, decomposing the space positioning error;
s4, combining a sag error compensation function of the numerical control system to construct a compensation data model of the space positioning error;
s5, compensating quality control is carried out on the correction coefficient based on a second-generation non-dominant sorting genetic algorithm, and optimization of the correction coefficient is achieved; which comprises the following steps:
s51, setting algorithm parameters and correction coefficient variation ranges;
s52, coding the machining center controller, and initializing a plurality of controller prevention schemes meeting constraints to form a population;
s53, calculating the time delay from the average processing tool to the controller, the time delay between the maximum controllers, the failure proportion of the average control path and the number of slave controllers of the average processing tool corresponding to each individual according to a preset data model and an objective function;
s54, performing non-dominant solution sequencing on the current population, and respectively calculating the crowding distance of individuals in each layer;
s55, selecting, crossing and mutating the population to generate a child population;
s56, merging the parent population and the offspring population according to elite retention strategy to obtain a next generation population;
s57, if the iteration number reaches the maximum iteration number, terminating the iteration and outputting an optimal correction coefficient;
s6, starting a range finder to calculate the distance between the machining tool and the workpiece, and outputting a current position signal of the workpiece by combining the optimized correction coefficient;
s7, the controller controls the clamp to slide to a designated position, and a machining tool is used for precisely machining a workpiece;
s8, detecting a linkage track of the rotating shaft according to a preset period, setting a linkage track positioning error threshold value, and detecting the machining precision of the workpiece;
s9, updating the geometric error correction data to an error database regularly.
2. The CNC processing method of vacuum cavity sealing member based on the space positioning error model according to claim 1, wherein the identifying the geometric error of the rotating shaft by the laser interferometer to form an error database comprises the following steps:
s21, mounting a double-frequency laser interferometer in the direction of a coordinate axis of a machine tool to be measured;
s22, adjusting the laser head to enable the measuring axis to coincide with or be parallel to the displacement axis of the machine tool, and pre-aligning the light path;
s23, inputting measurement parameters after laser preheating, and moving the machine tool for measurement according to a preset measurement program;
s24, identifying geometric errors in a working section of the numerical control machine tool by adopting a nine-line method;
s25, synthesizing various geometric error data to construct an error database.
3. The CNC machining method for vacuum cavity sealing members based on a spatial positioning error model according to claim 2, wherein the identification of geometric errors in the working section of the numerical control machine tool by using a nine-wire method comprises the following steps:
s241, establishing a workbench coordinate model, and setting a point A (X i ,Y i ,Z i );
S242, when the fixed point A moves along the X-axis coordinate, measuring an X-direction movement error value, wherein the expression comprises:
Figure FDA0003788415560000031
represented by matrix, let
x }=[δ x (x) δ y (x) δ z (x) ε x (x) ε y (x) ε z (x)] T
Then
{Δ(X)}=[E x ]{δ x }
Figure FDA0003788415560000041
Wherein { delta } x -represents a set of x-direction errors;
δ x (x) Representing a linear displacement error;
δ y (x) And delta z (x) Respectively representing straightness errors in the y direction and the z direction;
ε x (x) Representing a roll error;
ε y (x) Representing pitch error;
ε z (x) Representing yaw error;
E x representing a coefficient matrix;
x, Y, Z the X-axis, Y-axis, Z-axis in the coordinate system, respectively;
X i 、Y i 、Z i coordinate values respectively representing the point a;
Figure FDA0003788415560000042
and->
Figure FDA0003788415560000043
X, Y, Z straightness is respectively expressed;
i represents that the value of the number of the coordinate axes is (1, 2, 3);
t represents matrix transposition;
s243, when the fixed point A moves along the Y-axis coordinate, measuring a Y-direction movement error value;
s244, when the fixed point A moves along the Z-axis coordinate, measuring a Z-direction movement error value;
s245, calculating the perpendicularity error by using the straightness error of each axis.
4. The vacuum cavity seal CNC machining method based on the spatial positioning error model according to claim 1, wherein the spatial positioning error is decomposed into linear and nonlinear correlations.
5. The CNC processing method of vacuum cavity sealing members based on a spatial positioning error model according to claim 4, wherein the constructing a spatial positioning error compensation data model by combining a sag error compensation function of a numerical control system comprises the following steps:
s41, correcting an ideal numerical control instruction by combining a linear related space positioning error;
s42, downloading the corrected ideal numerical control instruction to each controller, and outputting a cutter route;
s43, moving the processing cutter to a processing point according to the cutter route;
s44, constructing an actual movement route of the machining tool in a body coordinate system, and drawing a tool path;
s45, checking the tool path and the tool path, constructing a compensation data model of the space positioning error, and outputting a correction coefficient.
6. The CNC machining method of vacuum cavity seals based on a spatial positioning error model according to claim 5, wherein the expression of the objective function is:
minF(CP)=[f 1 (CP),f 2 (CP),f 3 (CP),-f 4 (CP)]
where minF (CP) represents the value of the objective function;
f 1 (CP) means minimizing the time delay of the machining tool to the controller;
f 2 (CP) means minimizing the time delay between controllers;
f 3 (CP) means minimizing a control path failure rate;
f 4 (CP) means maximizing the average machining tool possession slave controller number;
CP denotes a deployment scenario of the controller.
7. The CNC processing method of a vacuum chamber seal based on a spatial positioning error model according to claim 6, wherein the calculation formula of the crowding distance comprises:
Figure FDA0003788415560000051
wherein I (d) K ) Representing a crowding distance;
I(d 0 ) Representing an initial congestion distance;
i (k) m represents the value of the mth objective function of the kth individual in I;
Figure FDA0003788415560000061
representing the maximum of the mth objective function;
Figure FDA0003788415560000062
representing the minimum of the mth objective function;
m represents the number of objective functions.
CN202210953009.9A 2022-08-09 2022-08-09 CNC (computer numerical control) processing method for vacuum cavity sealing piece based on space positioning error model Active CN115179445B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210953009.9A CN115179445B (en) 2022-08-09 2022-08-09 CNC (computer numerical control) processing method for vacuum cavity sealing piece based on space positioning error model

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210953009.9A CN115179445B (en) 2022-08-09 2022-08-09 CNC (computer numerical control) processing method for vacuum cavity sealing piece based on space positioning error model

Publications (2)

Publication Number Publication Date
CN115179445A CN115179445A (en) 2022-10-14
CN115179445B true CN115179445B (en) 2023-06-27

Family

ID=83523316

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210953009.9A Active CN115179445B (en) 2022-08-09 2022-08-09 CNC (computer numerical control) processing method for vacuum cavity sealing piece based on space positioning error model

Country Status (1)

Country Link
CN (1) CN115179445B (en)

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108959787A (en) * 2018-07-12 2018-12-07 山东大学 Consider the thermal deformation prediction technique and system of the macro dual drive system of actual condition
CN208880250U (en) * 2018-10-12 2019-05-21 永得利科技(无锡)有限公司 Vacuum gripper device for numerical control machining center
CN110109418A (en) * 2019-05-19 2019-08-09 重庆理工大学 A kind of geometric error Fast Identification Method of five face machining center of large-sized gantry
CN111665784A (en) * 2020-05-15 2020-09-15 成都飞机工业(集团)有限责任公司 Siemens subsystem-based spatial positioning error compensation method
CN112526927A (en) * 2021-02-18 2021-03-19 成都飞机工业(集团)有限责任公司 Quick optimization compensation method for space positioning error of rotating shaft of five-axis numerical control machine tool
CN112558547A (en) * 2021-02-19 2021-03-26 成都飞机工业(集团)有限责任公司 Quick optimization method for geometric error compensation data of translational shaft of five-axis numerical control machine tool

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108959787A (en) * 2018-07-12 2018-12-07 山东大学 Consider the thermal deformation prediction technique and system of the macro dual drive system of actual condition
CN208880250U (en) * 2018-10-12 2019-05-21 永得利科技(无锡)有限公司 Vacuum gripper device for numerical control machining center
CN110109418A (en) * 2019-05-19 2019-08-09 重庆理工大学 A kind of geometric error Fast Identification Method of five face machining center of large-sized gantry
CN111665784A (en) * 2020-05-15 2020-09-15 成都飞机工业(集团)有限责任公司 Siemens subsystem-based spatial positioning error compensation method
CN112526927A (en) * 2021-02-18 2021-03-19 成都飞机工业(集团)有限责任公司 Quick optimization compensation method for space positioning error of rotating shaft of five-axis numerical control machine tool
CN112558547A (en) * 2021-02-19 2021-03-26 成都飞机工业(集团)有限责任公司 Quick optimization method for geometric error compensation data of translational shaft of five-axis numerical control machine tool

Also Published As

Publication number Publication date
CN115179445A (en) 2022-10-14

Similar Documents

Publication Publication Date Title
CN108908327B (en) Robot positioning error grading compensation method
CN112526927B (en) Quick optimization compensation method for space positioning error of rotating shaft of five-axis numerical control machine tool
US20240019839A1 (en) Methods for quickly optimizing geometric error compensation data of translational axes of five-axis numerically controlled machine tools
US20120265331A1 (en) Five-axis flank milling system for machining curved surface and the tool-path planning method thereof
CN109129482B (en) Method for dynamically compensating motion error of linear guide rail of robot
ElMaraghy et al. Integrated inspection and machining for maximum conformance to design tolerances
CN114131611B (en) Off-line compensation method, system and terminal for joint errors of robot gravity pose decomposition
Li et al. Reference trajectory modification based on spatial iterative learning for contour control of two-axis NC systems
CN112536797A (en) Comprehensive compensation method for position and attitude errors of industrial robot
CN111897224B (en) Multi-agent formation control method based on actor-critic reinforcement learning and fuzzy logic
CN112733296A (en) GRNN-based milling error prediction and compensation method for hybrid robot
Jiang et al. A minimal-error-model based two-step kinematic calibration methodology for redundantly actuated parallel manipulators: An application to a 3-DOF spindle head
Gao et al. Kinematic calibration for industrial robots using articulated arm coordinate machines
CN115179445B (en) CNC (computer numerical control) processing method for vacuum cavity sealing piece based on space positioning error model
Zhang et al. Experimental analysis on the effectiveness of kinematic error compensation methods for serial industrial robots
CN113910001B (en) Numerical control machine tool space error identification method
Li et al. Data-driven industrial robot arm calibration: a machine learning perspective
CN114839921A (en) Five-axis contour control method based on data driving
CN112720480B (en) Robot track correction method and system based on grading errors
CN112318511A (en) Mechanical arm trajectory tracking control method based on data driving
Wan et al. Non-geometric error compensation for long-stroke cartesian robot with semi-analytical beam deformation and gaussian process regression model
CN113211436B (en) Six-degree-of-freedom series robot error calibration method based on genetic algorithm
Dong et al. Cross-coupling indirect iterative learning control method for batch processes with time-varying uncertainties
CN113183146A (en) Mechanical arm motion planning method based on rapid, flexible and all-pure embedding idea
Barari et al. Integrated inspection and machining approach to machining error compensation: advantages and limitations

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant